class_docstr: RawNet3 encoder. Extracts frame-level RawNet embeddings from raw waveform.
  paper: J. Jung et al., "Pushing the limits of raw waveform speaker
      recognition", in Proc. INTERSPEECH, 2022.
  
  Args:
      input_size: input feature dimension.
      block: type of encoder block class to use.
      model_scale: scale value of the Res2Net architecture.
      ndim: dimensionality of the hidden representation.
      output_size: ouptut embedding dimension.
code: def output_size(self) -> int:
      return self._output_size
  
file_path: espnet/espnet2/spk/encoder/rawnet3_encoder.py
imports: import torch
  import torch.nn
  from typeguard import check_argument_types
  from espnet2.asr.encoder.abs_encoder import AbsEncoder
  from espnet2.spk.layers.rawnet_block import Bottle2neck
label_desc: Use image node_id 2 for calling the RawNet3Encoder obj's underlying member method code with example usage: obj.output_size() and returns: self